Deck 15: Multiple Regression and Model Building

Question 1

A simple exponential forecasting method would not be used to forecast seasonal data.

Answer 1

True

Question 2

Removing the seasonal effect by dividing the actual time series observation by the estimated seasonal factor associated with the time series observation is called deseasonalization.

Answer 2

True

Question 3

Holt-Winters double exponential smoothing would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Answer 3

True

Question 4

When deseasonalizing a time series observation,the actual time series observation is divided by its seasonal factor.

Question 5

A Paasche index more accurately provides a year-to-year comparison of the annual cost of selected products in the market-basket than a Laspeyres index.

Question 6

A univariate time-series model is used to predict future values of a time series based only upon past values of a time series.

Question 7

While a simple index is calculated by using the values of one time series,an aggregate index is computed based on the accumulated values of more than one time series.

Question 8

The smoothing constant is a number that determines how much weight is attached to each observation.

Question 9

Cyclical variation exists when the magnitude of the seasonal swing does not depend on the level of a time series.

Question 10

The forecaster who uses MSD (mean squared deviations)to measure the effectiveness of forecasting methods would prefer method 1,which results in several smaller forecast errors,to method 2,which results in one large forecast error equal to the sum of the absolute values of several small forecast errors given by method 1.

Question 11

Exponential smoothing is a forecasting method that applies equal weights to the time series observations.

Question 12

A time series decomposition method would not be used to forecast seasonal data.

Question 13

The simple moving average method is primarily useful in determining the impact of trend on a time series.

Question 14

Dummy variable regression would be an appropriate method to use to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns.

Question 15

A positive autocorrelation implies that negative error terms will be followed by negative error terms.

Question 16

When using moving averages to estimate the seasonal factors,we need to compute the centered moving average if there are an odd number of seasons.

Question 17

Forecasters using a multiplicative decomposition model or time series regression model,assume that the time series components are changing over time.

Question 18

Dummy variables are used to model increasing seasonal variation.

Question 19

Trend refers to a long-run upward or downward movement of a time series over a period of time.

Question 20

Simple exponential smoothing is an appropriate method for prediction purposes when there is a significant trend present in a time series.

Question 21

The no-trend time series model is given by

A) TR_t = B₀ + B_1t.
B) TR_t = B₀.
C) TR_t = B₀ + B_1t + B_2t².
D) TR_t= B₀ + B_ln(t).

Question 22

Seasonal variations are periodic patterns in a time series that must last at least one year.

Question 23

In the Durbin-Watson test,if the calculated d-statistic is greater than the upper value of the d-statistic,then

A) we do not reject H₀,which says the error terms are not autocorrelated.
B) we do reject H₀,which says the error terms are not autocorrelated.
C) the test is inconclusive.
D) we do reject H₀,which says the error terms are positively or negatively autocorrelated.

Question 24

The multiplicative Winters method is used to forecast time series when there are no seasonal factors that are part of the model.

Question 25

A restaurant has been experiencing higher sales during the weekends,compared to the weekdays.Daily restaurant sales patterns for this restaurant over a week are an example of a(n)_________ component of a time series.

A) trend
B) seasonal
C) cyclical
D) irregular

Question 26

The Box-Jenkins methodology can be used to identify what is called an autoregressive-moving average model.

Question 27

If the errors produced by a forecasting method for 3 observations are +3,+3,and −3,then what is the mean squared error?

A) 9
B) 0
C) 3
D) −3
E) 2

Question 28

Causal variables can be used in forecasting models.

Question 29

Multiplicative decompositions assumes that time series components remain essentially constant over time.

Question 30

Exponential smoothing is designed to forecast time series described by regular and seasonal components that are always changing over time.

Question 31

The multiplicative Winters' method used to forecast time series applies a seasonal factor SN_T to the forecasting model..

Question 32

Simple exponential smoothing is a forecasting method that applies equal weights to the time series observations.

Question 33

Box-Jenkins methodology is a more sophisticated approach to forecasting a time series with components that might be changing over time.

Question 34

All of the following are forecasting methods except

A) Holt-Winters double exponential smoothing.
B) simple exponential smoothing.
C) time series regression.
D) MAD autocorrelation.

Question 35

When a forecaster uses the _________________ method,she or he assumes that the time series components are changing quickly over time.

A) time series regression
B) simple exponential smoothing
C) Box-Jenkins
D) multiplicative decomposition

Question 36

Random shock is a value that is assumed to have been randomly selected that is the same for each and every time period.

Question 37

Three criteria used to compare two forecasting methods are the mean absolute deviation,the mean squared deviation,and the mean absolute percentage error.

Question 38

If the errors produced by a forecasting method for 3 observations are +3,+3,and −3,then what is the mean absolute deviation?

A) 9
B) 0
C) 3
D) −3

Question 39

Which of the following is not a component of time series?

A) trend
B) seasonal
C) cyclical
D) irregular
E) smoothing constant

Question 40

When a forecaster uses the ______________ method,she or he assumes that the time series components are changing slowly over time.

A) time series regression
B) exponential smoothing
C) index number
D) multiplicative decomposition

Question 41

A major drawback of the aggregate price index is that

A) it does not take into account the fact that some items in the market basket are purchased more frequently than others.
B) it is difficult to compute.
C) it is computed by using the values from a single time series or based on a single product.
D) percentage comparisons cannot be made to the base year.

Question 42

Since a(n)____________ index employs the base-period quantities in all succeeding periods,it allows for ready comparisons for identical quantities of goods purchased between the base period and all succeeding periods.

A) simple
B) aggregate
C) Laspeyres
D) Paasche
E) quantity

Question 43

In the multiplicative decomposition method,the centered moving averages provide an estimate of

A) trend × seasonal.
B) trend × cycle.
C) seasonal × cycle.
D) trend × irregular.
E) seasonal × irregular.

Question 44

The ___________ component of a time series consists of erratic and unsystematic fluctuations in the time series data.

A) trend
B) seasonal
C) cyclical
D) irregular

Question 45

Suppose that the unadjusted seasonal factor for the month of April is 1.10.The sum of the 12 months' unadjusted seasonal factor values is 12.18.The normalized (adjusted)seasonal factor value for April

A) is larger than 1.1.
B) is smaller than 1.1.
C) is equal to 1.1.
D) cannot be determined with the information provided.

Question 46

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.Use this equation to forecast the demand for this product,and then calculate the MAD.

A) MAD = 1.333
B) MAD = 1.6
C) MAD = 2.0
D) MAD = 2.333
E) MAD = 2.5

Question 47

When the moving average method is used to estimate the seasonal factors with quarterly sales data,a ______ period moving average is used.

A) 2
B) 3
C) 4
D) 5
E) 8

Question 48

A sequence of values of some variable or composite of variables taken at successive,uninterrupted time periods is called a

A) least squares (linear)trend line.
B) moving average.
C) cyclical component.
D) time series.
E) seasonal factor.

Question 49

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.What are the forecast errors for the 5th and 6th years?

A) 0,−3
B) 0,+3
C) +2,+5
D) −2,−5
E) −1,−4

Question 50

Which of the following time series forecasting methods would not be used to forecast a time series that exhibits a linear trend with no seasonal or cyclical patterns?

A) dummy variable regression
B) linear trend regression
C) Holt-Winters double exponential smoothing
D) multiplicative Winters method
E) both dummy variable regression and multiplicative Winters method

Question 51

The demand for a product for the last six years has been 15,15,17,18,20,and 19.The manager wants to predict the demand for this time series using the following simple linear trend equation: tr_t = 12 + 2t.Use this equation to forecast the demand for this product,and then calculate the MSD.

A) MSD = 6
B) MSD = 3.3333
C) MSD = 7.0
D) MSD = 2
E) MSD = 2.4

Question 52

The ________ component of a time series measures the fluctuations in a time series due to economic conditions of prosperity and recession with a duration of approximately 2 years or longer.

A) trend
B) seasonal
C) cyclical
D) irregular

Question 53

The ___________ component of a time series refers to the erratic time series movements that follow no recognizable or regular pattern.

A) trend
B) seasonal
C) cyclical
D) irregular

Question 54

Which of the following time series forecasting methods would not be used to forecast seasonal data?

A) dummy variable regression
B) simple exponential smoothing
C) time series decomposition
D) multiplicative Winters method

Question 55

Those fluctuations that are associated with climate,holidays,and related activities are referred to as __________ variations.

A) trend
B) seasonal
C) cyclical
D) irregular

Question 56

When using simple exponential smoothing,the value of the smoothing constant α cannot be

A) negative.
B) greater than zero.
C) greater than 1.
D) .99.
E) negative or greater than 1.

Question 57

In general,the number of dummy variables used to model constant seasonal variation is equal to the number of

A) seasons.
B) seasons minus 1.
C) seasons plus 1.
D) seasons minus 2.
E) seasons divided by two.

Question 58

The ___________ component of a time series reflects the long-run decline or growth in a time series.

A) trend
B) seasonal
C) cyclical
D) irregular

Question 59

When the magnitude of the seasonal swing does not depend on the level of a time series,we call this _________ variation.

A) increasing seasonal
B) cyclical seasonal
C) constant seasonal
D) decreasing seasonal
E) no seasonal

Question 60

When there is _______________ seasonal variation,the magnitude of the seasonal swing does not depend on the level of the time series.

A) cyclical
B) constant
C) irregular
D) increasing

Question 61

When using simple exponential smoothing,the more recent the time series observation,the ____________ its corresponding weight.

A) larger
B) smaller
C) more irregular
D) more cyclical

Question 62

A positive autocorrelation implies that negative error terms will be followed by _________ error terms.

A) negative
B) positive
C) either negative or positive
D) irregular

Question 63

Weighting in exponential smoothing is accomplished by using _____________.

A) first-order autocorrelation
B) smoothing constants
C) the Durbin-Watson method
D) multiplicative decomposing

Question 64

If a time series exhibits increasing seasonal variation,one approach is to first use a(n)______________ transformation that produces a transformed time series that exhibits constant seasonal variation.Then,_________ variables can be used to model the time series with constant seasonal variation.

A) autocorrelation,dummy
B) fractional power,dummy
C) fractional power,constant
D) autocorrelation,constant

Question 65

In the multiplicative decomposition method,the centered moving averages provide an estimate of a trend's ____________.

A) index
B) cycle
C) seasonal variation
D) irregular variation

Question 66

The upward or downward movement that characterizes a time series over a period of time is referred to as _____________.

A) seasonal variation
B) cyclical variation
C) a trend
D) irregular variation

Question 67

When preparing a price index based on multiple products,if the price of each product is weighted by the quantity of the product purchased in a given period of time,the resulting index is called a ___________ price index.

A) Paasche
B) weighted aggregate
C) Laspeyres
D) cyclical (seasonal)

Question 68

When there is first-order autocorrelation,the error term in period t is related to the error term in period ______.

A) t
B) t + 1
C) t − 1
D) t − 2

Question 69

When deseasonalizing a time series observation,we divide the actual time series observation by its ___________.

A) irregular factor
B) cyclical factor
C) seasonal factor
D) weighted aggregate factor

Question 70

Periodic patterns in time series that repeat themselves within a calendar year or less are referred to as _____________.

A) constant variations
B) cyclical variations
C) seasonal variations
D) regular variations

Question 71

The ___________ test is a test for first-order positive autocorrelation.

A) Durbin-Watson
B) MSD
C) MAD
D) multiplicative Winters

Question 72

A _______________ index is most useful if the base quantities provide a reasonable representation of consumption patterns in succeeding time periods.

A) Paasche
B) weighted aggregate
C) Laspeyres
D) cyclical (seasonal)

Question 73

The Holt-Winters double exponential smoothing method is used to forecast time series data with ___________.

A) autocorrelation
B) a linear trend
C) cyclical patterns
D) moving averages

Question 74

The purpose behind moving averages and centered moving averages is to eliminate __________________.

A) constant variation
B) cyclical variation
C) seasonal variation
D) regular variation

Question 75

A forecasting method that weights recent observations more heavily is called _____________.

A) time series analysis
B) first-order autocorrelation
C) multiplicative decomposition
D) exponential smoothing

Question 76

A simple index is computed by using the values of one time series,while a(n)___________ index is based on a "market basket" consisting of more than one time series.

A) weighted
B) aggregate
C) cyclical
D) trend

Question 77

The Durbin-Watson statistic is used to detect _____________.

A) first-order autocorrelation
B) exponential smoothing
C) multiplicative decomposing
D) irregular variation

Question 78

A simple index is obtained by dividing the current value of a time series by the value of a time series in the _____________ time period and by multiplying this ratio by 100.

A) base
B) final
C) current
D) shortest

Question 79

The basic difference between MAD and MSE is that MSE,unlike MAD,penalizes a forecasting technique much more for _________ errors than for _________ errors.

A) large,small
B) small,large
C) small,zero
D) zero,large

Question 80

The recurring up-and-down movement of a time series around trend levels that last more than one calendar year is called ____________.

A) constant variation
B) cyclical variation
C) seasonal variation
D) irregular variation